A Tutorial Review of the Solar Power Curve: Regressions, Model Chains, and Their Hybridization and Probabilistic Extensions

Owing to the persisting hype in pushing toward global carbon neutrality,the study scope of atmospheric science is rapidly expanding.Among numerous trending topics,energy meteorology has been attracting the most attention hitherto.One essential skill of solar energy meteorologists is solar power curve modeling,which seeks to map irradiance and auxiliary weather variables to solar power,by statistical and/or physical means.In this regard,this tutorial review aims to deliver a complete overview of those fundamental scientific and engineering principles pertaining to the solar power curve.Solar power curves can be modeled in two primary ways,one of regression and the other of model chain.Both classes of modeling approaches,alongside their hybridization and probabilistic extensions,which allow accuracy improvement and uncertainty quantification,are scrutinized and contrasted thoroughly in this review.

Rolling Decision Model of Thermal Power Retrofit and Generation Expansion Planning Considering Carbon Emissions and Power Balance Risk

With the increasing urgency of the carbon emission reduction task,the generation expansion planning process needs to add carbon emission risk constraints,in addition to considering the level of power adequacy.However,methods for quantifying and assessing carbon emissions and operational risks are lacking.It results in excessive carbon emissions and frequent load-shedding on some days,although meeting annual carbon emission reduction targets.First,in response to the above problems,carbon emission and power balance risk assessment indicators and assessment methods,were proposed to quantify electricity abundance and carbon emission risk level of power planning scenarios,considering power supply regulation and renewable energy fluctuation characteristics.Secondly,building on traditional two-tier models for low-carbon power planning,including investment decisions and operational simulations,considering carbon emissions and power balance risks in lower-tier operational simulations,a two-tier rolling model for thermal power retrofit and generation expansion planning was established.The model includes an investment tier and operation assessment tier and makes year-by-year decisions on the number of thermal power units to be retrofitted and the type and capacity of units to be commissioned.Finally,the rationality and validity of the model were verified through an example analysis,a small-scale power supply system in a certain region is taken as an example.The model can significantly reduce the number of days of carbon emissions risk and ensure that the power balance risk is within the safe limit.

Prediction models of the ionization coefficient and ionization cross-section based on multi-layer molecular parameters

Prediction models were proposed to estimate the reduced Townsend ionization coefficient and ionization cross-section.A shape function of the reduced Townsend ionization coefficient curves was derived from the ionization collision probability model.The function had three parameters:the first ionization potential energy,A_(α),and B_(α).A_(α)and B_(α)were related to the molecule symmetry and size.The polarization of molecules could characterize the molecule symmetry.The multi-layer molecular cross-section(MMCS)was proposed to describe the contributions of electrons and molecule radius on different molecule surfaces to collisions.A prediction model of the ionization cross-section was also proposed based on Aα.The molecule parameters were calculated by the Becke3–Lee–Yang–Parr(B3LYP)method and the 6–311G**basis set.We used available data of 30 and 23 gases,respectively,to build the prediction models of reduced Townsend ionization coefficients and ionization cross-sections.The relationships between the molecular parameters Aαand Bαand the ionization cross-section were built up via nonlinear fittings.The determination coefficients R^(2)of Aα,Bα,and the ionization cross-section were 0.877,0.887,and 0.838,respectively.The results showed that the accuracy of models was positively correlated with the molecule symmetry and reduced electric field.This was mainly related to the accuracy of the MMCS model in predicting Aα.The MMCS model needed to be improved to describe the collision direction selectivity caused by the molecule asymmetry.Under a high reduced electric field,that error of Aαhad less influence on the prediction results.However,the prediction results for single atoms with high symmetry were poor.This may be due to the absolute error of the model close to single atoms’reduced Townsend ionization coefficients.The models could provide the basis for gas insulation prediction and discharge calculations,especially for symmetric molecules under a high electric field.

Impact of the Foucault Current and Its Vibration Noise Reduction on Bracket Features for AMDT

This manuscript explores the influences of the Foucault current on bracket vibration. Noise measurements are obtained in conditions that the coils are enclosed by the bracket, and exposed to the air for confirming the impact of Foucault current on bracket vibration. The outcomes illustrate that the bracket increases the primary noise to 21 d B. Throughout investigational modal computation, ordinary frequencies of the coils stay afar from the exciting frequency of 100 Hz but the ordinary frequency 72.924 Hz of the bracket stands near to 100 Hz, which similarly explicates the upsurge of the noise level. To do the computations on bracket vibrations instigated by the Foucault current, a finite-element method(FEM) has been utilized for evaluating the eddy current density, electromagnetic forces(EMF), coupled with bracket response in frequency domain. The calculations displayed a proper approval by mean of theoretic investigations, and the simulations analyzed effectively the bracket vibration produced by Eddy current, and the electromagnetic force(EMF). Referring to the simulation, the primary vibration characteristics, and noise level, the method by applying weights(stress) on the top bracket of transformer is proposed to lessen the vibration amplitude, and noise level. To indorse the utility, and application of the suggested technique, the experiment results are obtained, analyzed, and compared with those of simulations, primary vibration characteristics, and noise level.

Fault diagnosis of rolling bearings with noise signal based on modified kernel principal component analysis and DC‐ResNet

In view of the influence of aliasing noise on the effectiveness and accuracy of bearing fault diagnosis,a bearing fault diagnosis algorithm based on the spatial decoupling method of modified kernel principal component analysis(MKPCA)and the residual network with deformable convolution(DC‐ResNet)is innovatively proposed.Firstly,the Gaussian noise with different signal‐to‐noise ratios(SNRs)is added to the data to simulate the different degrees of noise in the actual data acquisition process.The MKPCA is used to project the fault signal with different SNRs in the kernel space to reduce the data dimension and eliminate some noise effects.Finally,the DC‐ResNet model is used to further filter the noise effects and fully extract the fault features through the training of the preprocessed data.The proposed algorithm is tested on the Case Western Reserve University(CWRU)and Xi'an Jiaotong University and Changxing Sumyoung Technology Co.,Ltd.(XJTU‐SY)bearing data sets with different SNR noise.The fault diagnosis accuracy can reach 100%within 30 min,which has better performance than most of the existing methods.The experimental results show that the algorithm has an excellent effect on accuracy and computation complexity under different noise levels.

Novel camera calibration method based on invariance of collinear points and pole-polar constraint

To address the eccentric error of circular marks in camera calibration,a circle location method based on the invariance of collinear points and pole–polar constraint is proposed in this paper.Firstly,the centers of the ellipses are extracted,and the real concentric circle center projection equation is established by exploiting the cross ratio invariance of the collinear points.Subsequently,since the infinite lines passing through the centers of the marks are parallel,the other center projection coordinates are expressed as the solution problem of linear equations.The problem of projection deviation caused by using the center of the ellipse as the real circle center projection is addressed,and the results are utilized as the true image points to achieve the high precision camera calibration.As demonstrated by the simulations and practical experiments,the proposed method performs a better location and calibration performance by achieving the actual center projection of circular marks.The relevant results confirm the precision and robustness of the proposed approach.

Extraction and analysis of tree canopy height information in high-voltage transmission-line corridors by using integrated optical remote sensing and LiDAR

Traditional inspection methods cannot quickly and accurately monitor tree barriers and safeguard the transmission lines.To solve these problems,in this study,we proposed a rapid canopy height information extraction method using optical remote sensing and LiDAR,and used UAV optical imagery with LiDAR to monitor the height of trees in a university and a high-voltage transmission line corridor in the Ningxia region.The results showed that the relative error of tree height extraction using UAV optical images was less than 5%,and the lowest relative error was 0.11%.The determination coefficient R^(2) between the optical image tree height extraction results and the measured tree height was 0.97,thus indicating a high correlation for both.In the field of tree barrier monitoring,the determination coefficient R^(2) of tree height extracted using airborne LiDAR point cloud,and canopy height model(CHM)and of the measured tree height were 0.947 and 0.931,respectively.The maximum and minimum relative error in tree height extraction performed using point cloud was 2.91%and 0.2%,respectively,with an extraction accuracy of over 95%.The experimental results demonstrated that it is feasible to use UAV optical remote sensing and LiDAR in monitoring tree barriers and tree height information extraction quickly and accurately,which is of great significance for the risk assessment and early warning of tree barriers in transmission-line corridors.

Optimal dispatching strategy for residential demand response considering load participation

To facilitate the coordinated and large-scale participation of residential flexible loads in demand response(DR),a load aggregator(LA)can integrate these loads for scheduling.In this study,a residential DR optimization scheduling strategy was formulated considering the participation of flexible loads in DR.First,based on the operational characteristics of flexible loads such as electric vehicles,air conditioners,and dishwashers,their DR participation,the base to calculate the compensation price to users,was determined by considering these loads as virtual energy storage.It was quantified based on the state of virtual energy storage during each time slot.Second,flexible loads were clustered using the K-means algorithm,considering the typical operational and behavioral characteristics as the cluster centroid.Finally,the LA scheduling strategy was implemented by introducing a DR mechanism based on the directrix load.The simulation results demonstrate that the proposed DR approach can effectively reduce peak loads and fill valleys,thereby improving the load management performance.

Optimal Cooperative Secondary Control for Islanded DC Microgrids via a Fully Actuated Approach

DC-DC converter-based multi-bus DC microgrids(MGs) in series have received much attention, where the conflict between voltage recovery and current balancing has been a hot topic. The lack of models that accurately portray the electrical characteristics of actual MGs while is controller design-friendly has kept the issue active. To this end, this paper establishes a large-signal model containing the comprehensive dynamical behavior of the DC MGs based on the theory of high-order fully actuated systems, and proposes distributed optimal control based on this. The proposed secondary control method can achieve the two goals of voltage recovery and current sharing for multi-bus DC MGs. Additionally, the simple structure of the proposed approach is similar to one based on droop control, which allows this control technique to be easily implemented in a variety of modern microgrids with different configurations. In contrast to existing studies, the process of controller design in this paper is closely tied to the actual dynamics of the MGs. It is a prominent feature that enables engineers to customize the performance metrics of the system. In addition, the analysis of the stability of the closed-loop DC microgrid system, as well as the optimality and consensus of current sharing are given. Finally, a scaled-down solar and battery-based microgrid prototype with maximum power point tracking controller is developed in the laboratory to experimentally test the efficacy of the proposed control method.

Numerical studies for plasmas of a linear plasma device HIT-PSI with geometry modified SOLPS-ITER

The HIT-PSI is a linear plasma device built for physically simulating the high heat flux environment of future reactor divertors to test/develop advanced target plate materials.In this study,the geometry-modified SOLPS-ITER program is employed to examine the effects of the magnetic field strength and neutral pressure in the device on the heat flux experienced by the target plate of the HIT-PSI device.The findings of the numerical simulation indicate a positive correlation between the magnetic field strength and the heat flux density.Conversely,there is a negative correlation observed between the heat flux density and the neutral pressure.When the magnetic field strength at the axis exceeds 1 tesla and the neutral pressure falls below 10 Pa,the HIT-PSI has the capability to attain a heat flux of 10 MW·m-2 at the target plate.The simulation results offer a valuable point of reference for subsequent experiments at HIT-PSI.

A Novel Method for Aging Prediction of Railway Catenary Based on Improved Kalman Filter

The aging prediction of railway catenary is of profound significance for ensuring the regular operation of electrified trains.However,in real-world scenarios,accurate predictions are challenging due to various interferences.This paper addresses this challenge by proposing a novel method for predicting the aging of railway catenary based on an improved Kalman filter(KF).The proposed method focuses on modifying the priori state estimate covariance and measurement error covariance of the KF to enhance accuracy in complex environments.By comparing the optimal displacement value with the theoretically calculated value based on the thermal expansion effect of metals,it becomes possible to ascertain the aging status of the catenary.To improve prediction accuracy,a railway catenary aging prediction model is constructed by integrating the Takagi-Sugeno(T-S)fuzzy neural network(FNN)and KF.In this model,an adaptive training method is introduced,allowing the FNN to use fewer fuzzy rules.The inputs of the model include time,temperature,and historical displacement,while the output is the predicted displacement.Furthermore,the KF is enhanced by modifying its prior state estimate covariance and measurement error covariance.These modifications contribute to more accurate predictions.Lastly,a low-power experimental platform based on FPGA is implemented to verify the effectiveness of the proposed method.The test results demonstrate that the proposed method outperforms the compared method,showcasing its superior performance.

A New Method of Wind Turbine Bearing Fault Diagnosis Based on Multi-Masking Empirical Mode Decomposition and Fuzzy C-Means Clustering

Based on Multi-Masking Empirical Mode Decomposition (MMEMD) and fuzzy c-means (FCM) clustering, a new method of wind turbine bearing fault diagnosis FCM-MMEMD is proposed, which can determine the fault accurately and timely. First, FCM clustering is employed to classify the data into different clusters, which helps to estimate whether there is a fault and how many fault types there are. If fault signals exist, the fault vibration signals are then demodulated and decomposed into different frequency bands by MMEMD in order to be analyzed further. In order to overcome the mode mixing defect of empirical mode decomposition (EMD), a novel method called MMEMD is proposed. It is an improvement to masking empirical mode decomposition (MEMD). By adding multi-masking signals to the signals to be decomposed in different levels, it can restrain low-frequency components from mixing in highfrequency components effectively in the sifting process and then suppress the mode mixing. It has the advantages of easy implementation and strong ability of suppressing modal mixing. The fault type is determined by Hilbert envelope finally. The results of simulation signal decomposition showed the high performance of MMEMD. Experiments of bearing fault diagnosis in wind turbine bearing fault diagnosis proved the validity and high accuracy of the new method.

Random vibration analysis of switching apparatus based on Monte Carlo method

The performance in vibration environment of switching apparatus containing mechanical contact is an important element when judging the apparatus’s reliability. A piecewise linear two-degrees-of-freedom mathematical model considering contact loss was built in this work, and the vibration performance of the model under random external Gaussian white noise excitation was investigated by using Monte Carlo simulation in Matlab/Simulink. Simulation showed that the spectral content and statistical characters of the contact force coincided strongly with reality. The random vibration character of the contact system was solved using time (numerical) domain simulation in this paper. Conclusions reached here are of great importance for reliability design of switching apparatus.

Numerical simulation of electro-magnetic and flow fields of TiAl melt under electric field

This article aims at building an electromagnetic and fluid model, based on the Maxwell equations and Navier-Stokes equations, in TiAl melt under two electric fields.FEM (Finite Element Method) and APDL (ANSYS Parametric Design Language) were employed to perform the simulation, model setup, loading and problem solving.The melt in molds of same cross section area with different flakiness ratio (i.e.width/depth) under the load of sinusoidal current or pulse current was analyzed to obtain the distribution of electromagnetic field and flow field.The results show that the induced magnetic field occupies sufficiently the domain of the melt in the mold with a flakiness ratio of 5:1.The melt is driven bipolarly from the center in each electric field.It is also found that the pulse electric field actuates the TiAl melt to flow stronger than what the sinusoidal electric field does.

Method of reliability tolerance design based on EDA technology and its application on DC hybrid contactor

Tolerance design, including tolerance analysis and distribution, is an important part of the electronic system’s reli- ability design. The traditional design needs to construct mathematic model of material circuit, which involves large amount of workload and lacks of practicability. This paper discusses the basic theory of electronic system’s reliability tolerance design and presents a new design method based on EDA (Electronic Design Automatic) software. This method has been validated through the application research on reliability tolerance design of the DC hybrid contactor’s control circuit.

Application of a Current and Voltage Mixed Control Mode for the New Fast Control Power Supply at EAST

A feedback control system is needed to restrain plasma vertical displacement in EAST （Experimental Advanced Superconducting Toknmak）. A fast control power supply excites active feedback coils, which produces a magnetic field to control the plasma＇s displacement. With the development of EAST, new demands on the new fast control power supply have led to an enhanced ability of fast response and output current, as well as a new control mode. The structure of cascaded and paralleled H-bridges can meet the demand of extended capacity, and digital control can reMize current and voltage mixed control mode. The validity of the proposed scheme is confirmed by experiments.

Prediction of elevator traffic flow based on SVM and phase space reconstruction

To make elevator group control system better follow the change of elevator traffic flow (ETF) in order to adjust the control strategy,the prediction method of support vector machine (SVM) in combination with phase space reconstruction has been proposed for ETF.Firstly,the phase space reconstruction for elevator traffic flow time series (ETFTS) is processed.Secondly,the small data set method is applied to calculate the largest Lyapunov exponent to judge the chaotic property of ETF.Then prediction model of ETFTS based on SVM is founded.Finally,the method is applied to predict the time series for the incoming and outgoing passenger flow respectively using ETF data collected in some building.Meanwhile,it is compared with RBF neural network model.Simulation results show that the trend of factual traffic flow is better followed by predictive traffic flow.SVM algorithm has much better prediction performance.The fitting and prediction of ETF with better effect are realized.

Effects of Gamma-Ray Irradiation on Dielectric Surface Breakdown of Polybutylene Naphthalate and Polybutylene Terephthalate Under Reduced Pressure

With the increasing application of electric and electronic devices in space and nuclear power stations, the polymeric insulation materials are inevitably exposed to various kinds of environments. Accordingly, it becomes necessary to investigate the effects of the radiation and air pressure on insulation materials. This paper describes the effects of gamma-ray irradiation and reduced pressure on dielectric breakdown of polybutylene naphthalate (PBN) and polybutylene terephthalate (PBT) by applying a DC pulse voltage. Both PBN and PBT were irradiated in air up to 100 kGy and then up to 1 000 kGy with a dose rate of 10 kGy/h by using a60Co gamma-source. The effects of total dose and reduced pressure on the time to dielectric breakdown and discharge quantity were discussed. Obtained results show that, while increasing the total dose, the discharge quantity decreased with PBN, but increased with PBT. With decreasing the air pressure, the discharge quantity increased with PBN, but decreased with PBT. With increasing the total dose, the time to dielectric breakdown increased with PBN, but decreased with PBT. With decreasing the air pressure, the time to dielectric breakdown increased with both PBN and PBT. The experimental results suggest that the chemical structure of polybutylene polymers plays a main role in the result of radiation reaction, which is related to cross-linking and degradation reaction.

Thermodynamic Properties and Transport Coefficients of Nitrogen,Hydrogen and Helium Plasma Mixed with Silver Vapor

Species composites of Ag-N2, Ag-H2 and Ag-He plasmas in the temperature range of 3,000-20,000 K and at 1 atmospheric pressure were calculated by using the minimization of Gibbs free energy. Thermodynamic properties and transport coefficients of nitrogen, hydrogen and helium plasmas mixed with a variety of silver vapor were then calculated based on the equilibrium composites and collision integral data. The calculation procedure was verified by comparing the results obtained in this paper with the published transport coefficients on the case of pure nitrogen plasma. The influences of the silver vapor concentration on composites, thermodynamic properties and transport coefficients were finally analyzed and summarized for all the three types of plasmas. Those physical properties were important for theoretical study and numerical calculation on arc plasma generated by silver-based electrodes in those gases in sealed electromagnetic relays and contacts.

Adaptive synchronization control of coupled chaotic neurons in an external electrical stimulation

In this paper we present a combined algorithm for the synchronization control of two gap junction coupled chaotic FitzHugh-Nagumo （FHN） neurons in an external electrical stimulation. The controller consists of a combination of dynam- ical sliding mode control and adaptive backstepping control. The combined algorithm yields an adaptive dynamical sliding mode control law which has the advantage over static sliding mode-based controllers of being chattering-free, i.e., a suffi- ciently smooth control input signal is generated. It is shown that the proposed control scheme can not only compensate for the system uncertainty, but also guarantee the stability of the synchronized error system. In addition, numerical simulations are also performed to demonstrate the effectiveness of the proposed adaptive controller.